Weight gain and obesity have reached alarming levels throughout the developed world. Over 30% of Americans are obese and 1.4 billion adults worldwide are overweight. Obesity is a risk factor for numerous metabolic diseases and accounts for ~$147 billion in health care costs each year in the United States. The greatest increase in prevalence of obesity rates occurs in the college-aged population, an age that is a critical developmental time period for establishing long-term health behaviors. Eating during the night and variable sleep-wake timing are novel potential risk factors for weight gain and obesity, yet little is known about how these risk factors influence weight and obesity in the college-aged population. We have recently found that the number of meals college students consume after 2000h is associated with a higher percentage of body fat relative to weight. However, more detail is needed on the relationship between the timing of meals with circadian physiology and sleep-wake behaviors as: (i) the circadian phase in college students is delayed as compared to older populations and thus 2000h may not be the circadian night (i.e., when melatonin is elevated); (ii) composition of meals at specific times of the day could differently affect body composition; and (iii) variable sleep-wake timing may influence the timing of food intake. We therefore propose an experiment to identify the association of both meal and sleep-wake timing variability with weight, body composition, and meal composition in college undergraduates. This study will be a supplement to a currently funded NIH R01 project on the effects of social networks on sleep in college students. For that study, each student participates for 1-month while at school by: (i) completing online diaries twice daily about sleep-wake patterns; (ii) wearing sensors that monitor sleep and wakefulness; (iii) allowing an application on their mobile phone to track phone and internet usage; and (iv) staying overnight at our facility to assess melatonin onset (a marker of circadian phase and the time at which the circadian system begins to promote sleep). For this supplement, we will also track the timing and content of food consumed using a time-stamped mobile phone food diary for a 7-day period and record their weight and body composition (percent body fat). Sleep variability will be assessed using the daily online sleep-wake diaries and wearable sensors that measure daily sleep timing and duration. The results from the proposed work will allow us to quantify relationships among eating at inappropriate circadian times, sleep-wake timing variability, weight, body composition, and meal composition. Identifying potential modifiable behaviors (e.g., timing of meals and sleep) to reduce weight levels in this population is crucial for developing research based strategies for decreasing the burdens and high cost of disease during adulthood. The results will provide additional information about the relationships between circadian rhythms, sleep-wake behavior, and metabolism. The knowledge can be utilized in public health forums, including educational campaigns about food timing and its effects on body composition.